QuasarDB is an ultra-high-performance, cost-effective solution for demanding timeseries data challenges. QuasarDB has been designed to pick up the slack where data warehousing fails: large scale, write-heavy, timeseries workloads in financial and manufacturing applications. QuasarDB takes the problem from the edge to the cloud, including domain-specific solutions. For example, order book management or signal pre-processing in predictive maintenance.
We believe a modern data infrastructure should deliver the impossible: low-latency queries on a huge dataset. Stop wasting time and money on the wrong tools; give QuasarDB a try!
Timeseries data grows exponentially. Is your infrastructure ready? QuasarDB is the truly scalable timeseries solution that can ingest hundreds of megabytes per second while delivering sub-millisecond queries.
QuasarDB currently solves hard manufacturing and finance problems such as predictive maintenance or real-time introspection into financial markets (e.g., Nasdaq full order book). It is an end-to-end platform with the features, tools, and practices to wire in your time-critical queries.
QuasarDB runs everywhere, from 32-bit ARM devices to high-end Intel servers, from Edge Computing to the cloud or on-premises. Queries are written in familiar SQL. QuasarDB supports many programming languages and integrates seamlessly with most BI, streaming, and visualization software.
QuasarDB is the most cost-effective timeseries solution, thanks to its ultra-efficient resource usage, the capability to leverage object storage fo (S3), unique compression technology, and fair pricing model. We charge you on RAM usage: storage and cores are unlimited!
Turnkey solutions perfectly configured by our experts. Our managed instances include: ingestion, analytics connectivity, backups, replication, and monitoring.Learn More
Do-it-yourself QuasarDB. Run QuasarDB in your datacenter or your embedded device. The On-premises option has a free community edition. This community edition is fully featured and has no time limit.Learn More